Papers
4
Total Citations
98
H-Index
2
About
Ciyu Ruan is a rising researcher at the intersection of robotic perception, computer vision, and embodied intelligence. Their work focuses on solving fundamental perception challenges for autonomous systems, particularly in grasping, high-speed tracking, and event-based vision. Ruan’s most impactful contribution is **GraspNeRF**, the first multiview RGB-based 6-DoF grasp detection method for transparent and specular objects—a notoriously difficult problem due to depth camera failures. By leveraging generalizable Neural Radiance Fields, this work overcomes geometric sensing limitations and has already garnered 91 citations, establishing a new paradigm for vision-based robotic manipulation. Ruan also pioneers event camera research for mobile robotics, with **EventTracker** achieving low-latency 3D localization of high-speed objects by fusing event and depth data, and their 2025 work on event-based abstraction and acceleration for drones and agile robots. These contributions address critical gaps in high-agility embodied perception, pushing the boundaries of what autonomous agents can perceive and interact with in real time. Ruan’s research is shaping the future of robotic systems that must operate reliably in challenging, dynamic environments.
Research Focus
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Top Papers
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